Unbalanced Distribution Feeders Research Articles

An Optimized Strategy for the Integration of Photovoltaic Systems and Electric Vehicles into the Real Distribution Grid

The increasing spread of photovoltaic systems for private households (PVs) and electric vehicles (EVs) in order to reduce carbon emissions significantly impacts operation conditions in existing distribution networks. Variable and unpredictable PVs can stress distribution network operation, mainly manifested in voltage violations during the day. On the other hand, variable loads such as EV chargers which have battery storage in their configuration have the ability of storying a surplus energy and, if it is necessary, support a distribution network with energy, commonly known as vehicle-to-grid concept (V2G), to help voltage stability network enhancement. This paper proposes an optimal power flow (OPF)-based model for EV charging to minimize power exchange between the superior-10 kV grid and the observed distribution feeder. The optimization procedure is realized using the co-simulation approach that connects power flow analysis software and optimization method. Three different scenarios are observed and analysed. The first scenario is referred to as a base case without optimization. The second and third scenarios include optimal EV charging and discharging patterns under different constraints. To test the optimization model, a 90-bus unbalanced distribution feeder modelled based on real-life examples is used. The obtained results suggest that this optimization model does not only significantly reduce the power exchange between an external network and the distribution feeder but also improves voltage stability and demand curve in the distribution feeder.

Increasing Unbalanced Distribution Network’s Hosting Capacity for Distributed Energy Resources by Voltage Regulators

Renewable energy sources (RESs) are becoming promising nowadays. Deploying distributed energy resources (DERs) is thus increasing accordingly, but the intermittent nature associated with RES remains a significant challenge. Also, the distribution grid faces technological difficulties with the large-scale integration of PV generations and EV charging loads. This paper suggests a strategy for a novel optimal voltage regulator (VR) placement model associated with the optimal placement of electric vehicle chargers (EVCs) and photovoltaic (PV) cells. Also, VRs’ reference voltages are determined optimally to enhance the hosting capacity (HC) of three-phase unbalanced distribution feeders for large-scale residential/public EVCs and PVs. Two scenarios are defined to study the impact of VRs on the network’s HC for DERs, namely with and without VRs in the real three-phase unbalanced feeder. The developed model determines the optimal placement of VRs and their reference voltages linked with EVCs and PVs penetration. Time-Varying Acceleration Coefficients Iteration Particle Swarm Optimization (TVAC-IPSO) algorithm has been implemented to improve the real three-phase unbalanced distribution feeder’s HC for DERs. The efficiency of the proposed model and the solution method is validated on the modified IEEE 37-node medium voltage (MV) radial distribution network connected to 35 low voltage (LV) distribution feeders. The obtained results represent that installing a proper number of VRs will increase the network’s HC for DERs.

Distribution Feeder Parameter Estimation Without Synchronized Phasor Measurement by Using Radial Basis Function Neural Networks and Multi-Run Optimization Method

In practice, the performance of distribution feeder parameter estimation is limited by the measurement conditions in distribution networks. An accurate mathematical model that considers limited phasor measurements in distribution networks is necessary to estimate feeder parameters. This paper presents a set of modified parameter estimation models for unbalanced three-phase distribution feeders that only require the measurements of voltage amplitudes and power flows. To simplify the calculation process and improve the estimated results, a method combined with a radial basis function neural network (RBFNN) and multi-run optimization method (MRO), namely RBFNN-MRO, is proposed to calculate the parameters of distribution feeders. The relationship between the feeder parameters and the measurement data from the two terminals of the feeder can be mapped perfectly using the RBFNN. Furthermore, the random errors in the measurement device were eliminated using the proposed RBFNN-MRO algorithm. The RBFNN-MRO algorithm can limit the number of neurons in the hidden layer and substantially reduce the training time for each RBFNN. The feasibility of the proposed method was verified using four IEEE test systems. The proposed RBFNN-MRO and RBFNN methods were compared using the maximum absolute percentage error (MAPE) curves. The results reveal that the proposed RBFNN-MRO method has excellent potential for improving the accuracy of feeder parameter estimation even without synchronized phasor measurement.

Three‐phase feeder parameter estimation using radial basis function neural networks and multi‐run optimisation method with bad data preparation

The difference between the actual feeder parameters and feeder parameter data stored in a database or offered by manufacturers is significant owing to the ambient environment, temperature, and skin effect. Here, a parameter estimation method is proposed for unbalanced three-phase distribution feeders based on the bus voltages and branch power flows measured from two terminals of the feeder. In the proposed method, a high-precision phasor measurement unit is not required to estimate the magnitude and phase angle of the phasor quantity using a common time source for synchronisation. A radial basis function neural network with multi-run optimisation (RBFNN-MRO) is proposed to map the complex nonlinear relations between the distribution feeder parameters and electrical quantities. The feasibility and performance of the proposed RBFNN-MRO method were verified using the four IEEE test systems. The comparison between the proposed RBFNN-MRO method and the multi-run method based on the quasi-Newton method is implemented via the maximum absolute percentage error (MAPE) curves. The results reveal that the proposed RBFNN-MRO method has excellent potential for improving the accuracy of feeder parameter estimation, even for bad data preparation.

Cooperative Peak Shaving and Voltage Regulation in Unbalanced Distribution Feeders

This paper considers the co-operation of distributed generators (DGs), battery energy storage systems (BESSs) and voltage regulating devices for integrated peak shaving and voltage regulation in distribution grids through a co-optimization framework, which aims to minimize the operational costs while fulfilling the operational constraints of network and devices. To account for the uncertainties of load demand and generation, we then convert the co-optimization model into a two-stage stochastic program where state-of-charge (SoC) trajectories of BESSs and operation of voltage regulating devices are optimized at the first stage for day-ahead scheduling, while the reactive powers of DGs and BESSs are left at the second stage for potential intra-day scheduling to handle short-term voltage issues. The proposed co-optimization scheme is validated on the IEEE 37-node test feeder and compared with other practices.

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems.

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

Stochastic multi-period optimal dispatch of energy storage in unbalanced distribution feeders

This paper presents a convex, multi-period, AC-feasible Optimal Power Flow (OPF) framework that robustly dispatches flexible demand-side resources in unbalanced distribution feeders against uncertainty in very-short timescale solar Photo-Voltaic (PV) forecasts. This is valuable for power systems with significant behind-the-meter solar PV generation as their operation is affected by uncertainty from forecasts of demand and solar PV generation. The aim of this work is then to ensure the feasibility and reliability of distribution system operation under high solar PV penetration. We develop and present a novel, robust OPF formulation that accounts for both the nonlinear power flow constraints and the uncertainty in forecasts. This is achieved by linearizing an optimal trajectory and using first-order methods to systematically tighten voltage bounds. Case studies on a realistic distribution feeder shows the effectiveness of a receding-horizon implementation.

Optimal Multi-Period Dispatch of Distributed Energy Resources in Unbalanced Distribution Feeders

This paper presents an efficient algorithm for the multi-period optimal dispatch of deterministic inverter-interfaced energy storage in an unbalanced distribution feeder with significant solar PV penetration. The three-phase, non-convex loss-minimization problem is formulated as a convex second-order cone program (SOCP) for the dispatch of batteries in a receding-horizon fashion in order to counter against the variable, renewable generation. The solution of the SOCP is used to initialize a nonlinear program (NLP) in order to ensure a physically realizable solution. The phenomenon of simultaneous charging and discharging of batteries is rigorously analyzed and conditions are derived that guarantee it is avoided. Simulation scenarios are implemented with GridLab-D for the IEEE-13 and IEEE-123 node test feeders and illustrate not only AC feasibility of the solution, but also near-optimal performance and solve-times within a minute.

Dynamic Microgrids With Self-Organized Grid-Forming Inverters in Unbalanced Distribution Feeders

In contrast to conventional static microgrids (MGs), MGs with dynamic and adjustable territories (i.e., dynamic MGs) are proposed and implemented in this article. Dynamic MGs are commonly dominated by grid-forming inverters and nested in unbalanced distribution feeders. Unlike balanced systems where only positive-sequence components exist, proper operation of unbalanced dynamic MGs presents additional challenges. A distributed secondary control strategy is developed in this article for distributed generators (DGs) interfaced with grid-forming inverters in unbalanced dynamic MGs by providing coordinated regulations on both positive- and negative-sequence system models. System frequency and voltage are under constant regulation, along with voltage unbalance (VU) management for multiple critical load buses (CLBs). The proposed control strategy enables seamless system transition during unbalanced dynamic MGs reconfiguration and guarantees proportional positive- and negative-sequence power-sharing among connected DGs with respect to system topology variation. Detailed controller designs are provided and stability analyses are derived. The proposed control strategy is fully implemented in hardware controllers and validated on a hardware-in-the-loop (HIL) MG testbed.

Fault location of unbalanced power distribution feeder with distributed generation using neural networks

In this study, a modified version of IEEE 34-bus test feeder with two fixed speed wind generators is considered. In the proposed method, at first, the type of short circuit is determined using the 3-phase current data that are measured at the substation. Then, to train and test the Artificial Neural Network (ANN), different operating patterns are produced for each type of short circuit. In order to cover the total operating space of the radial distribution network by ANNs; fault location, fault resistance, load of every node and power of distributed generations DGs are changed in each pattern. For each type of short circuit, three different ANNs are used for estimation of the distance of fault to the substation and the interconnection of DGs. Inputs of the ANNs are 3-phase voltage and current which measured at the substation and the DG buses in pre fault and post fault stages. The results show low estimation error in testing of ANNs. For exact fault location, the estimated fault distance to the substation is compared with the estimated fault distance to the DG buses. Finally, the sensitivity of ANNs to the measuring error of the input data is examined.

Harmonic Distortion Minimization in Power Grids with Wind and Electric Vehicles

Power-electronic interfacing based devices such as wind generators (WGs) and electrical vehicles (EVs) cause harmonic distortions on the power grid. Higher penetration and uncoordinated operation of WGs and EVs can lead to voltage and current harmonic distortions, which may exceed IEEE limits. It is interesting to note that WGs and EVs have some common harmonic profiles. Therefore, when EVs are connected to the grid, the harmonic pollution EVs impart onto the grid can be reduced to some extent by the amount of wind power injecting into the grid and vice versa. In this context, this work studies the impact of EVs on harmonic distortions and careful utilization of wind power to minimize the distortions in distribution feeders. For this, a harmonic unbalanced distribution feeder model is developed in OpenDSS and interfaced with Genetic Algorithm (GA) based optimization algorithm in MATLAB to solve optimal harmonic power flow (OHPF) problems. The developed OHPF model is first used to study impact of EV penetration on current/voltage total harmonic distortions (THDs) in distribution grids. Next, dispatch of WGs are found at different locations on the distribution grid to demonstrate reduction in the current/voltage THDs when EVs are charging.

루프운전 배전선로의 고장계산 방법

Loop system arrangement in the primary distribution system has been increased for higher reliability of power supply to the customer. This paper presents a new fault calculation method for the loop structured unbalanced distribution feeders. Mathematical modeling method of the distribution system and superposition principal based fault calculation procedures are provided. In order to establish feasibility of the proposed method, various case studies have been performed using Matlab power system toolbox.

Loss minimization using optimal allocation of photovoltaic units in unbalanced radial distribution feeders: A case study

The very mounting demand for the electricity supply and the raising concern about global warming and climate change have motivated the electricity sector to adopt renewable and local sources of energy. The incorporation of such sources into the distribution network poses a variety of benefits as well as challenges to the Distribution System Operators. The paper analyses a real life 4.3 MVA unbalanced distribution feeder in Kerala, India for its voltage profile improvement and power loss reduction with the addition of Photovoltaic (PV) units at the specified locations with optimal sizing. A methodology based on the Learning Automata (LA) algorithm is developed in order to find out the suitable size of the PV units to be installed at suitable locations in an unbalanced distribution feeder. The LA algorithm is efficient in handling the uncertainty associated with the PV power generation which is modelled using Beta Probability Density Function. The proposed algorithm is validated using the balanced feeder in the literature and extended for several unbalanced test feeders and the selected practical distribution feeder.

A New Method for Online Sensitivity-Based Distributed Voltage Control and Short Circuit Analysis of Unbalanced Distribution Feeders

Reactive power support through shunt capacitors and distributed generation is used in conjunction with step voltage regulators (SVRs) for voltage control of distribution feeders. Distribution management system is responsible for coordination among distributed reactive power sources, such as capacitors, photovoltaic and wind power generators, and SVRs. In this paper, a novel method for calculating voltage sensitivity to active, reactive power injection, and SVR taps in unbalanced distribution feeders is developed. The method is based on ABCD parameters of network components which are used in forward/backward sweep of power-flow solution. The method can deal with network unbalance, network shunt admittances, single-phase sections, and ungrounded sections. The initial sensitivities are calculated in one power-flow forward sweep through a recursive way, and the online updating of sensitivities is very easy and straightforward so the method is suitable for online voltage control. A novel sensitivity-based online optimization method is developed for online coordinated voltage control with no prior information about the load. The same ABCD parameters are used for developing a novel method for calculating short circuit currents in unbalanced distribution feeders. The method can also handle unbalance, shunt elements, and single phase sections, and is applicable to all fault types. The developed method for voltage control and short circuit calculation are tested on the IEEE comprehensive test feeder and the results prove the effectiveness of the proposed algorithms.

Volt/var optimization of unbalanced distribution feeders via mixed integer linear programming

The paper presents a Mixed Integer Linear Programming (MILP) model for the solution of the three-phase volt/var optimization (WO) of medium voltage unbalanced distribution feeders. The WO of a distribution feeder is aimed at calculating the most efficient operating conditions by means of the scheduling of transformers equipped with an on-load tap changer and distributed reactive power resources (such as embedded generators and switchable capacitors banks). The proposed model allows the representation of feeders composed by three-phase, two-phase, and single-phase lines, by transformers with different winding connections, by unbalanced wye- and delta-connected loads, by three-phase and single phase capacitor banks and embedded generators. The accuracy of the results is verified by using IEEE Test Feeders.

Combined compensation structure of a static Var compensator and an active filter for unbalanced three-phase distribution feeders with harmonic distortion

A combined reactive power compensation method of a static Var compensator (SVC) and an active filter is described in this paper for unbalanced three-phase distribution feeders with harmonic distortion. The SVC acts as a classic reactive power compensator for load balancing and power factor correction. The small rating active filter is used to improve filtering characteristics of the passive filter in SVC and suppress possible resonance between the system impedance and the passive filter. The control signals are derived from the calculation of instantaneous active and reactive powers of the distribution feeder. Simulation results carried out by the electromagnetic transients program (EMTP) show that the proposed reactive power compensation configurations can effectively balance currents, correct power factor, and eliminate harmonic currents.

Harmonic impedance measurement using three-phase transients

In this paper, a technique is presented for measuring the harmonic impedances of an unbalanced three-phase distribution feeder. The technique uses transients in bus voltages and feeder currents generated by several close-trip operations of the shunt capacitor bank. The work is based on the assumption that the impedance of the feeder does not change over time during which the switching operations are performed. Mathematical development of the technique is verified with the laboratory and the field tests. The technique provided good measurements of the harmonic impedances up to 1.5 kHz for the given capacitor sizes. Statistical indices were developed to assess the accuracy of the estimated impedance values.

Distribution feeder line models

Starting with a modified version of Carson's equations, this paper develops distribution feeder models that can be used in the power flow and short circuit analysis of unbalanced three-phase distribution feeders. A simple line section is used to demonstrate the differences in voltage drops that occur between the various models for load conditions varying from balanced to very unbalanced.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>